From Nomads to Settlers: Scenario analysis as a guide for first home owners in renting versus buying a home in Perth, Western Australia.
Bibliographic record
Abstract
The number of nationwide First Home Owner Grant (FHOG) purchases was 54,924; in the June quarter of 2009, an increase of 94.3% over the year (REIA 2009). This paper outlines an analysis tool which compares the financial outcomes for households who are contemplating the tenure choice of renting versus buying their first home in the Perth metropolitan region with the FHOG. The model employs the user cost of capital theory to develop a model that calculates the relative cost of renting and buying for a variety of house types under a number of market growth scenarios.. The results indicate that purchasing a median priced house has an immediate net financial benefit when compared to renting a house at the median rent if the annual growth rate for the property is ≥2.95% .This model can be used by prospective purchases to aid the decision to rent or purchase using either pre-determined scenarios based on historic variable rates or employing user generated assumptions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".